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Estimation and Control Problems for Stochastic Partial Differential Equations

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Release : 2013-09-17
Genre : Mathematics
Kind : eBook
Book Rating : 860/5 ( reviews)

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Book Synopsis Estimation and Control Problems for Stochastic Partial Differential Equations by : Pavel S. Knopov

Download or read book Estimation and Control Problems for Stochastic Partial Differential Equations written by Pavel S. Knopov. This book was released on 2013-09-17. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partial differential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents research that has not previously been covered. More generally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics. The models presented describe many processes in turbulence theory, fluid mechanics, hydrology, astronomy, and meteorology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to applied mathematicians who use probability and statistical methods in the selection of useful signals subject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monograph can be used for education courses on the estimation and control theory of random fields.

Mathematical Control Theory for Stochastic Partial Differential Equations

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Release : 2021-10-19
Genre : Science
Kind : eBook
Book Rating : 318/5 ( reviews)

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Book Synopsis Mathematical Control Theory for Stochastic Partial Differential Equations by : Qi Lü

Download or read book Mathematical Control Theory for Stochastic Partial Differential Equations written by Qi Lü. This book was released on 2021-10-19. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for this type of system are explained in detail. Interestingly enough, one has to develop new mathematical tools to solve some problems in this field, such as the global Carleman estimate for stochastic partial differential equations and the stochastic transposition method for backward stochastic evolution equations. In a certain sense, the stochastic distributed parameter control system is the most general control system in the context of classical physics. Accordingly, studying this field may also yield valuable insights into quantum control systems. A basic grasp of functional analysis, partial differential equations, and control theory for deterministic systems is the only prerequisite for reading this book.

Deterministic and Stochastic Optimal Control and Inverse Problems

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Release : 2021-12-15
Genre : Computers
Kind : eBook
Book Rating : 723/5 ( reviews)

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Book Synopsis Deterministic and Stochastic Optimal Control and Inverse Problems by : Baasansuren Jadamba

Download or read book Deterministic and Stochastic Optimal Control and Inverse Problems written by Baasansuren Jadamba. This book was released on 2021-12-15. Available in PDF, EPUB and Kindle. Book excerpt: Inverse problems of identifying parameters and initial/boundary conditions in deterministic and stochastic partial differential equations constitute a vibrant and emerging research area that has found numerous applications. A related problem of paramount importance is the optimal control problem for stochastic differential equations. This edited volume comprises invited contributions from world-renowned researchers in the subject of control and inverse problems. There are several contributions on optimal control and inverse problems covering different aspects of the theory, numerical methods, and applications. Besides a unified presentation of the most recent and relevant developments, this volume also presents some survey articles to make the material self-contained. To maintain the highest level of scientific quality, all manuscripts have been thoroughly reviewed.

Parameter Estimation in Stochastic Differential Equations

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Release : 2007-09-26
Genre : Mathematics
Kind : eBook
Book Rating : 487/5 ( reviews)

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Book Synopsis Parameter Estimation in Stochastic Differential Equations by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Differential Equations written by Jaya P. N. Bishwal. This book was released on 2007-09-26. Available in PDF, EPUB and Kindle. Book excerpt: Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.

Stochastic Processes, Estimation, and Control

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Release : 2008-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 597/5 ( reviews)

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Book Synopsis Stochastic Processes, Estimation, and Control by : Jason L. Speyer

Download or read book Stochastic Processes, Estimation, and Control written by Jason L. Speyer. This book was released on 2008-01-01. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty and risk are integral to engineering because real systems have inherent ambiguities that arise naturally or due to our inability to model complex physics. The authors discuss probability theory, stochastic processes, estimation, and stochastic control strategies and show how probability can be used to model uncertainty in control and estimation problems. The material is practical and rich in research opportunities.

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